Super-Resolution Methods for Endoscopic Imaging: A Review

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dc.contributor.authorMansoor Hayat
dc.contributor.authorManoj Gupta
dc.contributor.authorPannee Suanpang
dc.contributor.authorAziz Nanthaamornphong
dc.contributor.correspondenceM. Hayat; Dept. of Electrical Engineering, Chulalongkorn University, Bangkok, Thailand; email: 6471015721@student.chula.ac.th
dc.date.accessioned2025-03-10T07:34:20Z
dc.date.available2025-03-10T07:34:20Z
dc.date.issued2024
dc.description.abstractThis review paper presents a comprehensive analysis of recent advancements in super-resolution applications in endoscopic imaging. It synthesizes findings from multiple cutting-edge research papers, each contributing unique methodologies and results. The review highlights the progression from traditional techniques to deep learning models, and attention mechanisms. Emphasis is placed on the practical application of these advancements in enhancing the quality of images for minimally invasive surgery, ultimately contributing to improved surgical outcomes. This synthesis not only showcases the current state of the field but also identifies potential areas for future research and development. © 2024 IEEE.
dc.identifier.citationIEMECON 2024 - 12th International Conference on Internet of Everything, Microwave, Embedded, Communication and Networks
dc.identifier.doi10.1109/IEMECON62401.2024.10846748
dc.identifier.isbn979-835038731-5
dc.identifier.scopus2-s2.0-85218133988
dc.identifier.urihttps://repository.dusit.ac.th//handle/123456789/4482
dc.languageEnglish
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.rights.holderScopus
dc.subjectendoscopic imaging
dc.subjectminimally invasive surgery
dc.subjectreview
dc.subjectsurgical outcomes
dc.titleSuper-Resolution Methods for Endoscopic Imaging: A Review
dc.typeConference paper
mods.location.urlhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85218133988&doi=10.1109%2fIEMECON62401.2024.10846748&partnerID=40&md5=7649381c1ad1c2549f1c0a8775e00795
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